strategies for gene discovery in schizophrenia
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Transcript strategies for gene discovery in schizophrenia
Genetics and Neuroimaging:
Current Findings and Future Strategies
James L Kennedy MD, FRCPC
I’Anson Professor of Psychiatry and Medical Science
Head, Neurogenetics Section, Clarke Division,
Director, Department of Neuroscience Research
Centre for Addiction and Mental Health (CAMH),
University of Toronto
& SG Potkin, D Mueller, M Masellis,
N Potapova, F Macciardi
How do genes determine brain characteristics?
Molecular Genetic Approach
Gene
Gene Expression
Pharmacogenetics
Variants
Pharmacology
Neurobiology
Phenotype
-Psychophysiology;
Neuroimaging
Endophenotype
Sub-pheno
Candidate gene selection for schizophrenia
• Neurotransmitter system genes
– e.g. dopamine receptors, transporter
• Neurodevelopmental genes
– Cortical development, patterning
– Neuronal differentiation, migration
– Synaptic protein genes
• Human post-mortem expression studies (Mirnics et al, 2000;
Vawter et al, 2001)
• Animal model expression studies (Wong et al, 2002; Barrett et al, 2003)
Dissect the neurotransmitter, synaptic machinery, myelin
system, etc, with molecular genetics… Neuroimaging will
help both hypothesis generation and validation of new
genetic findings
Cytoarchitectural abnormalities
Control
Schizophrenia
Comparison of
hippocampal pyramids at
the CA1 and CA2 interface
between control and
schizophrenic.
Cresyl violet stain,
original magnification X250
Conrad et al. (1991)
Arch Gen Psychiatry
TARDIVE DYSKINESIA
Symptoms of TD
TD is characterized by abnormal involuntary
movements of the lip, jaw and tongue.
Choreoathetoid movements of the extremities
and/or trunk may occur as well.
- Symptoms are
measured using
scales such as :
the Abnormal
Involuntary
Movement Scale
(AIMS) and the
Rockland Simpson
Scale (RSS).
- The AIMS scale
ranges from 0 - 40
and patients with
higher AIMS scores
have more severe
symptoms.
Motor effects
Cognitive
effects
Why DRD3 ?
• D3 mRNA and protein have been localized
to the ventral side of the striatum and the
ventral putamen (motor control) (Joyce &
MeadorWoodruff, 1997)
• D3 receptors have been shown to have an
inhibitory effect on locomotor activity in rats.
(Kling-Peterson et al, 1995)
•Evidence that the Msc I polymorphism of
DRD3 is functional: allelic differences display
different affinities for dopamine in vitro.
(Lundstrom & Turpin, 1996)
Neuroanatomical Distributions of
Dopamine Receptors
(Seeman etal, 1995)
Mean AIMS Scores for DRD3 Msc I Polymorphism
after Typical Neuroleptic Treatment
16
14
Mean
14.20
Corrected 12
Mean
10
AIMS
8
score
6
4
2
Mean
3.470
Mean
3.920
Ser/Ser
Ser/Gly
0
n=34
n=53
DRD3 Genotype
Gly/Gly
n=25
F[2,95] = 8.25, p < 0.0005 ( n = 112 ), Power = 0.568, r-square=0.297
(Bonferroni p < 0.0015)
(Basile et al, 1999)
Ethnically Stratified Means
Caucasian Means (N=85)
Afro-American Means (N=25)
14
9
10
Mean AIMS
Mean AIMS
12
8
6
4
2
33
43
Ser/Ser
Ser/Gly
0
Gly/Gly
Genotype
F[2,83]=3.85, p = 0.026
(Bonferroni p = 0.078)
16
14
12
10
8
6
4
2
0
16
9
Ser/Gl
Gly/Gl
Genotype
F[1,23]=8.10, p = 0.0091
(Bonferroni p = 0.009)
Brain Metabolism Following Haloperidol
Treatment by D3 Genotype (FDG, n=14)
Gly-Ser
& Ser-Ser
(n=9)
Haloperidol (5wks)
Baseline
Baseline
Gly-Gly
(n=5)
(UCI Brain Imaging Centre; Potkin, Kennedy & Basile, 2003)
CYP2D6 vs 1A2
(Shimoda et al, 1994)
(12.7%)
CYP1A2
(1.5%)
CYP2D6
Other
CYP2A6
- Metabolism is determined
by both affinity and
abundance relative to the
total liver P450 content.
CYP2B6
CYP2C
CYP3A
CYP2E1
Note: CYP2D6 also
expressed in brain –
neuroimaging may capture
some of this variance
- 2D6 has a higher affinity for
most typicals, but it accounts
for only 2% of total liver
content.
2D6 is “high affinity-low
capacity”
-2D6 is not inducible; 1A2 is
Mean AIMS Scale Scores for DRD3 by CYP1A2 Genotype
25
20
Mean 15
AIMS
Score 10
C/C
5
A/C
A/A
0
Gly/Gly
Ser/Gly
CYP1A2 Genotype
Ser/Ser
DRD3 Genotype
Additive recessive model strongly supported compared to alternative models
Tardive Dyskinesia Summary :
- Given the numerous replications of the DRD3-TD finding, and the
PET neuroimaging validation, it appears that the dopamine D3
receptor is involved in TD susceptibility.
- The interaction between DRD3 and CYP1A2 genes fits a
recessive - recessive model with each gene interacting additively.
- The DRD3 and CYP1A2 results account for ~55% of the variance
in TD; other genes and environment may account for the rest.
??Clinical genetic test for TD risk in the future??
DOPAMINE D1 RECEPTOR
Dopamine D1 Receptor
D1
concentration
in PFC 10X
greater than
D2 (Lidow
1991)…
Important for
antipsychotic
action?
(Missale 1998)
Antipsychotic Binding Profiles
140
120
100
80
Ki (nmol/L)
D2
D1
60
40
20
0
Olanz
Cloz
Risp
Halo
(Kerwin 1996, in vitro tissue analyses)
Tauscher et al., 2004
D1 Receptor Blockade:
• D1 blockade by antipsychotics may
potentiate activity in the PFC by
disinhibiting NMDA receptor (Williams
1995)
D1
NMDA
Improvement of Symptoms
Cognition?
Dopamine D1 Gene (DRD1) (5q35.1)
Markers in 5’ upstream region may be implicated
in the regulation of D1 gene expression.
(-1251)
ERE
(-800)
(-48)
P2
P1
(+1403)
+1
+1341
Coding Region
Marker
Minor Allele
Frequency
-1251 (G/C)
0.14
Restriction
Enzyme
HaeIII
-800 (C/T)
0.32
HaeIII
-48 (A/G)
0.32
DdeI
+1403 (T/C)
0.33
Bsp1286I
DRD1, PET FDG, & Clozapine Response
Genotype 2/2
BPRS = 30%
Improvement
Genotype 1/2
BPRS = 7%
Genotype
Worsening1/2
(Potkin et al, 2002)
Clozapine Response Prediction
Algorithm?
• Arranz et al (2000) have reported a multi-gene
(n = 10+ markers) model for clozapine response in
one sample. Includes: D2, D4; 5HT1A, 2A, 2C, 4,
6; H1, H3,…
• Model must be replicated in a new sample to be
meaningful
• Neuroimaging as a augmenting phenotype in each
patient may provide valuable intermediary
information from the brain, allowing more
biologically meaningful subtyping.
Serotonin Transporter
5HTT specific ligand in PET
• 5HTT specific ligand for PET [11C]DASB
optimized in Toronto by radiochemist Alan
Wilson
• N = 20 medication-free depressed patients,
20 anxiety disorder, and 20 normal controls
underwent PET imaging with [11C]DASB
ligand; blood for genetics
• 5HTT gene typed for ins/del in promoter
and the VNTR in intron II
[11C] DASB Binding to 5HTT in
Depressives vs Normals by Genotype:
Frontal Region
14
12
10
nM
8
Depressed
Normals
6
4
2
0
del/del
del/ins
ins/ins
PET Ligand (DASB) 5HTT Binding Potential
correlates with Dysfunctional Attitude
[Meyer et al,
Toronto PET
Group,
Arch Gen
Psych, 2004]
Serotonin
Transporter
Ligand
Binding
Potential
5HTTLPR
genetic
marker does
not predict
5HTT
Binding
(Kennedy et
al, in prep)
N=20 Major Depressives
P < .001
Dysfunctional Attitude Scale Score
Will the Brain Derived Neurotrophic Factor
(BDNF) Gene Predict Grey Matter Volume?
BDNF-1 SNP
BDNF-2
Exon 11
Val-66-met
(GT)n repeat
(function? mRNA
stability)
BDNF-3
BDNF-4
BDNF val66met: MRI functional
brain imaging (Egan et al, Cell 2003)
The red/yellow areas
indicate brain regions
(primarily hippocampus)
that function differently
between val/val (n=8) and
val/met (n=5) subjects
while performing a working
memory task. Subjects with
the met allele had more
abnormal function.
Haplotype TDT: BDNF (GT)n repeat &
val66met in schizophrenia
*
26
30
25
20
Transmissions
Non Trans
15
12
10
10
5
7
5
5
6
2
0
-2
-2
-1
-1
1
3
3
1
lo
lo
lo
lo
p
p
p
p
Ha
Ha
Ha
Ha
* HTDT for 170-val66
c2 = 7.11; 1 df;
p = 0.007
Muglia et al, (2002)
Neurotrophic
Mechanisms
in Depression
Nestler et al, 2002
Bipolar Disorder: TDT studies show robust
effect of BDNF gene
• Combined Toronto sample (Neves-Pereira et al,
2002; N=300) plus MIT (Sklar et al, 2003) (N=200
+ 150 NIMH) for val66met yields p =
.0000001
• Phenotype dissection of our Toronto bipolar
sample shows association with rapid cycling,
non-suicidal, non-psychotic, earlier age at
onset subjects (Mueller et al, in preparation)
BDNF polymorphisms in Childhood Onset
Depression: Pittsburgh Sample
90
80
70
60
50
Cases
Controls
40
30
N=104 pairs;
c2=4.7;df=1;
p=0.03
20
10
0
met
Haplotype
p = 0.001
val
140
120
100
80
Cases
Controls
60
40
20
0
174
172
170
168
GT repeat alleles
166
N=104 pairs; c2= 17.8;
df=5; p= 0.0032
172 bp allele: OR = 0.55
168 bp allele: OR = 3.94
Hippocampal shape as a phenotype for
genetic studies
Figure 1d: Principal deformation for the right hippocampus for normal
controls (top) and schizophrenia patients (bottom). Four views (front,
lateral, back, medial) of each shape are shown. The color indicates the
direction and the magnitude of the deformation, changing from blue
(inwards) to green (no deformation) to red (outwards).
Will MOG gene variants predict
white matter abnormalities?
Prefrontal fMRI activity and myelin reduced in schizophrenia
Figure 3:1-4: Statistical parametric maps of the fractional anisotropy
(FA) (left) and Magnetic Transfer Ratio (MTR) (myelin) (right) group
comparison. Similar areas in yellow on both maps correspond to the
location of both the internal capsule and prefrontal white matter,
and indicate smaller values of FA and myelin in schizophrenia
patients (n=14) compared with controls (n=15).
Fractional Anisotropy
UNC
clustering
Bundle
selection
Hypothesis: MOG, MAG, MBP
genes will predict quantity or
distribution of myelinated tracts
Measurement
along tract
DTI New MRI Imaging Technique Reveals Brain Circuits
Cingulum
Corpus callosum
Dorsal
stream
Frontal striatial
projections
Fornix
Actual white matter tracks in
schizophrenic patient revealed
by DTI (colors and location by J. Fallon)
Complexities in Genetics &
Neuroimaging
• Genetic variants express themselves in
many ways – singularly, or combined
(haplotypes, epistasis, partial penetrance…)
• What are the appropriate phenotypes to use
from brain imaging data?
• How to control massive multiple testing of
genome scan x brain voxels (millions x
millions)?
Summary
• D3 gene link to tardive dyskinesia validated by
PET imaging
• D1 role in schizophrenia and clozapine response
supported by genetic variants and PET activity
pre/post clozapine
• BDNF gene candidate for grey matter measures?
• MOG gene candidate for white matter?
• Vast expanses of quality data await us: we only
need to develop our informatics sophistication…
National Alliance for Medical Imaging and Computing:
NAMIC
www.na-mic.org